PL-300 Practice Test 27 — 15 Questions

Question 1

Which THREE of the following are valid reasons to use a calculated column instead of a measure in Power BI?

Accepted Answer

The value is needed in a row-level security rule. Option A is correct because row-level security rules in Power BI (DAX filter expressions on tables) are evaluated at the row level and can reference calculated columns, whereas measures cannot be used directly in RLS filter predicates. Option C is correct because relationships between tables require a column on the "one" or "many" side, and calculated columns are stored in the model and can serve as relationship keys, while measures cannot participate in relationships. Option D is correct because slicers and filter fields require column values to populate their item lists, and a calculated column materializes those values at row level so it can be placed on the slicer or filter well, unlike a measure. Option B is not correct because aggregations that respond to user interaction are precisely the role of measures, which are evaluated dynamically per filter context. Option E is not correct because time intelligence calculations depending on the current filter context are dynamic and should be implemented as measures, not calculated columns, which are computed at refresh time and cannot adapt to slicer or filter changes.

Answer

The value is an aggregation (e.g., SUM) that changes with user interaction

Answer

The value is a time intelligence calculation that depends on the current filter context

Question 2

Which THREE features are available in Power BI to support natural language queries?

Accepted Answer

Suggested Questions. Suggested Questions (B) is correct because Power BI automatically generates natural-language question prompts for a dataset, letting report authors add them so users can click a question and get a Q&A visual result without typing. The Q&A visual (C) is correct because it is the core natural-language feature: users type questions in plain English (or another supported language) into the Q&A box and Power BI interprets them against the semantic model to produce charts and tables. Synonyms for tables and columns (D) is correct because defining synonyms in the model (via Model view or Q&A linguistic schema) improves Q&A's understanding of user terms, mapping words like 'revenue' to a column such as 'SalesAmount'. Key Influencers (A) is not a natural-language query feature; it is an AI visual that analyzes which factors influence a metric. Quick Measures (E) is not natural-language either; it is a dialog-driven way to generate DAX calculations from templates.

Answer

Key Influencers visual

Answer

Quick Measures

Question 3

You need to audit Power BI activity for compliance. Which tool should you use to access detailed logs of user actions?

Accepted Answer

Microsoft Purview compliance portal (Audit). The correct option is B, Microsoft Purview compliance portal (Audit), because it provides the unified audit log that captures detailed Power BI user activity such as viewed reports, edited datasets, shared dashboards, and exported data, which is exactly what a compliance audit requires. Power BI activity events are surfaced through the Microsoft 365 audit log, accessible via the Purview compliance portal's Audit search (or the Search-UnifiedAuditLog cmdlet), letting you filter by workload, user, and date. Option A, Microsoft Defender XDR, focuses on security incidents and threat detection across endpoints, identities, and email, not on Power BI activity auditing. Option C, Microsoft Purview Data Map, catalogs and classifies data assets for governance but does not record user action logs. Option D, the Power BI Premium capacity metrics app, reports on capacity utilization and performance metrics, not detailed per-user activity logs.

Answer

Microsoft Defender XDR

Answer

Microsoft Purview Data Map

Answer

Power BI Premium capacity metrics app

Question 4

You are a data analyst at a multinational retail company. The company uses Microsoft Power BI to analyze sales data from multiple regions. The source data is stored in Azure SQL Database and includes tables: Sales (OrderID, ProductID, Quantity, Amount, OrderDate, StoreID), Stores (StoreID, StoreName, Region, Country), Products (ProductID, ProductName, Category, Price). The model is imported daily. You need to design a semantic model that supports the following requirements: 1) Allow users to filter by year and month using a single slicer. 2) Ensure that time intelligence functions (e.g., TOTALYTD, SAMEPERIODLASTYEAR) work correctly. 3) Minimize model size. 4) Provide a consistent date dimension for all fact tables. The Sales table has orders from 2018-01-01 to 2025-12-31. You decide to create a date table. Which of the following approaches should you take?

Accepted Answer

Create a date table using DAX with CALENDAR and mark it as a date table.. Option A is correct because creating a dedicated date table with DAX CALENDAR (e.g., CALENDAR(DATE(2018,1,1), DATE(2025,12,31))) and marking it as a date table gives a single, contiguous date dimension that supports one slicer for year/month, enables time intelligence functions like TOTALYTD and SAMEPERIODLASTYEAR, and can be kept narrow to minimize model size. Marking it as a date table ensures Power BI treats it as the official date table for the model, providing consistent filtering across fact tables. Option B is wrong because using Sales[OrderDate] directly does not create a shared date dimension and calculated year/month columns add size without proper date-table semantics. Option C is wrong because auto-generated date hierarchies create hidden tables per date column, increasing model size and not providing one consistent date dimension. Option D is not the best fit because importing a full date table with additional attributes can add unnecessary columns and size, whereas the requirement emphasizes minimizing model size and a purpose-built DAX date table is sufficient.

Answer

Use the Sales[OrderDate] column directly and create a calculated column for year and month.

Answer

Use Power BI's auto-generated date hierarchy for each date column.

Answer

Import a date table from the source database that includes all dates and additional attributes.

Question 5

You are combining data from multiple Excel files stored in SharePoint Online. Each file has the same structure but different data. You need to create a solution that automatically includes new files added to the SharePoint folder without manual intervention. What should you use?

Accepted Answer

Use 'Get Data from SharePoint Online Folder' and then 'Combine files' transform.. The correct option is C: use 'Get Data from SharePoint Online Folder' and then the 'Combine files' transform. In Power Query, connecting to the SharePoint Online folder connector retrieves all files in that folder, and the 'Combine files' transform automatically applies the same parsing/template to every file, so newly added files with the same structure are included on refresh without manual work. Option A adds unnecessary copying to blob storage and still requires orchestration, while B is manual and defeats the automation requirement. Option D targets a SharePoint list rather than the folder's files and loads them separately, which does not automatically combine new files.

Answer

Use Power Automate to copy new files to a blob storage, then import from there.

Answer

Use 'Merge queries' to append each new file manually.

Answer

Use 'Get Data from SharePoint Online List' and load each file separately.

Question 6

Refer to the exhibit. You are reviewing a Power BI activity log entry. What action should you take to ensure compliance if the user who created the report should not have access to 'Confidential' data?

Accepted Answer

Investigate the user's permissions on the dataset 'SalesDataset' to verify they are authorized to access confidential data.. The correct action is C: investigate the user's permissions on the dataset 'SalesDataset' to verify they are authorized to access confidential data. In a Power BI activity log, a report creation event alone does not prove a compliance breach; the actual access control is enforced through the dataset's permissions and the sensitivity label applied to the data, so you must confirm whether the user legitimately has access to 'Confidential' data before taking any remediation. Option A is wrong because deleting the report is a destructive action that does not address the underlying permission issue and could destroy legitimate work. Option B is wrong because changing the sensitivity label to 'General' would misclassify the data and could itself create a compliance violation. Option D is wrong because simply ignoring the event fails to verify whether the user's access was authorized, which is the required compliance check.

Answer

Delete the report immediately.

Answer

Change the sensitivity label on the report to 'General'.

Answer

Ignore the event because the report creation is logged but not necessarily a violation.

Question 7

You need to design a data model for a sales analysis that includes measures for total sales, sales by product, and sales by customer. The source data has a 'Transactions' table with columns: TransactionID, Date, CustomerID, ProductID, Quantity, Amount. What is the recommended star schema design?

Accepted Answer

Create a fact table and separate dimensions for Date, Customer, and Product. Option B is correct because a star schema centers on a single fact table (here, Transactions with Quantity and Amount as measures) surrounded by separate dimension tables for Date, Customer, and Product, which lets you aggregate total sales and slice by product or customer efficiently. Keeping each dimension distinct preserves clean grain, supports conformed attributes, and enables the required sales-by-product and sales-by-customer analysis. Option A is wrong because splitting into two fact tables fragments the same transaction grain and complicates cross-measure analysis. Option C is wrong because a single denormalized table is not a star schema and loses dimensional modeling benefits. Option D is wrong because combining Customer and Product into one dimension creates a snowflake-like or junk dimension that prevents independent analysis by each attribute.

Answer

Create two fact tables: one for sales and one for customers

Answer

Create a single table with all columns

Answer

Create a fact table and one dimension containing Customer and Product

Question 8

You are a Power BI analyst for a financial services company. You have a semantic model that contains a 'Transactions' fact table with millions of rows, and a 'Calendar' date dimension table. You need to create a report page that shows the year-to-date (YTD) total transaction amount compared to the same period last year (SPLY). The report must allow users to select a year from a slicer, and the YTD calculation should always be based on the maximum date in the data for the selected year (i.e., show YTD as of the latest available date). You have created the following measures:

- Total Amount = SUM(Transactions[Amount])
- YTD Amount = TOTALYTD([Total Amount], 'Calendar'[Date])
- SPLY YTD = CALCULATE([YTD Amount], SAMEPERIODLASTYEAR('Calendar'[Date]))

When users select a year from the slicer, the YTD Amount does not correctly show the YTD as of the last date in the selected year; instead, it shows the YTD for each individual date in the context. What is the most likely issue?

Accepted Answer

The YTD measure should be wrapped in a CALCULATE that filters to the last date in the selected period.. The correct option is C: the YTD measure must be wrapped in a CALCULATE that filters the Calendar to the last date in the selected period, because TOTALYTD evaluates at whatever date granularity is in the current filter context, so on a visual by date it returns a running YTD per day rather than a single YTD-as-of-latest-date value. To force the measure to always show YTD as of the maximum date for the selected year, you need something like CALCULATE([YTD Amount], LASTDATE('Calendar'[Date])) (or FILTER to the max date), which overrides the row-level date context. Option A is wrong because an inactive relationship would break all time intelligence, not just the YTD granularity, and the scenario implies the Calendar relationship works. Option B is wrong because slicer-to-Calendar filtering is not the cause; the slicer already filters the year, and the issue is date-level context within the visual. Option D is wrong because DATESYTD is the underlying time-intelligence function TOTALYTD uses and would not by itself change the per-date evaluation behavior.

Answer

The relationship between Transactions and Calendar is not active.

Answer

The slicer is not configured to filter the Calendar table.

Answer

The TOTALYTD function is not appropriate; you should use DATESYTD instead.

Question 9

Which TWO actions can improve the performance of a Power BI report that uses DirectQuery? (Select two.)

Accepted Answer

Set up aggregations in the data source. Option A is correct because with DirectQuery, every visual interaction translates into queries sent to the underlying source, so defining user-defined aggregations (or aggregation tables) in the data source lets Power BI satisfy many queries from pre-aggregated summary tables instead of scanning detail rows, dramatically reducing query cost and latency. Option D is correct because each visual on a DirectQuery report page typically issues its own query (or queries) to the source, so reducing the number of visuals lowers the number of concurrent queries and the volume of data returned, improving render time and easing source load. Option B is not appropriate because calculated columns are computed and stored in the model at refresh time and, in DirectQuery, they are either unsupported for certain expressions or force row-by-row evaluation that cannot be pushed down, so they do not improve query performance. Option C is wrong because adding slicers increases the number of queries and filter combinations sent to the source, which adds latency rather than reducing it. Option E is wrong because the Power BI service cache applies to imported/refreshed datasets and cached tiles, not to DirectQuery queries that must hit the source live, so increasing cache size does not speed up DirectQuery reports.

Answer

Use calculated columns instead of measures

Answer

Add more slicers to allow users to filter data

Answer

Increase the cache size in the Power BI service

Question 10

You have a Power BI dataset that uses row-level security (RLS) with roles defined in Power BI Desktop. You publish the dataset to the Power BI service. Which TWO statements are true about RLS behavior?

Accepted Answer

Users assigned to a role will only see rows that satisfy the role's DAX filter.. Option B is correct because RLS in Power BI enforces row filtering through the DAX filter expression defined on each table in the role; when a user is assigned to that role, queries executed against the dataset return only the rows where the DAX predicate evaluates to TRUE. Option E is correct because roles are authored in Power BI Desktop, but user or group membership in those roles is assigned in the Power BI service (via the dataset's Security page or the Admin portal / REST API), since Desktop has no knowledge of the service's users and groups. Option A is not correct because RLS filters data at query time for viewers and does not change or affect the dataset's scheduled refresh process. Option C is not correct because RLS filters rows in the underlying tables, not visual titles or other report metadata, which are not automatically altered by RLS. Option D is not correct because RLS operates at the row level on tables, not at the measure level; restricting measures requires object-level security (OLS), which is a separate feature.

Answer

RLS affects the refresh schedule of the dataset.

Answer

Visual titles are automatically filtered based on RLS.

Answer

RLS can restrict access to specific measures.

Question 11

A Power BI administrator needs to audit which users have exported data from a specific report in the last 30 days. What is the most efficient way to retrieve this information?

Accepted Answer

Query the Power BI activity log using the audit log search in the Microsoft 365 Defender portal.. The correct option is C: query the Power BI activity log using the audit log search in the Microsoft 365 Defender portal, because Power BI audit events such as ExportReport, ExportData, and ExportToFile are centralized in the unified Microsoft 365 audit log, which supports filtering by user, date range, and activity type for the last 30 days. This is the most efficient way to identify exactly which users exported data from a specific report, since the audit log records per-user, per-item activity. Option A is not the right tool because Microsoft Purview compliance portal search is oriented toward compliance and eDiscovery scenarios rather than granular Power BI report export auditing. Option B only provides aggregated usage metrics (view counts and similar statistics) without per-user export detail. Option D is incorrect because Azure Monitor for Power BI Premium focuses on capacity and resource telemetry, not user-level export auditing.

Answer

Use the Microsoft Purview compliance portal to search for 'Export' events.

Answer

Check the report's usage metrics report for export counts.

Answer

Review the 'Export to Excel' metrics in the Azure Monitor for Power BI Premium.

Question 12

You are a Power BI administrator. Your organization uses Microsoft Purview to manage sensitivity labels. You need to ensure that when a report is exported to PDF, the sensitivity label is automatically applied to the PDF file. What should you configure?

Accepted Answer

Enable the tenant setting 'Apply sensitivity labels to exported data' in the Power BI admin portal.. Option A is correct because the Power BI tenant setting 'Apply sensitivity labels to exported data' (in the Power BI admin portal) is specifically what causes the sensitivity label on a report to be inherited by exported files such as PDF, PPTX, and XLSX. When this setting is enabled, Power BI propagates the report's label to the exported artifact so the PDF carries the same protection. Option B is incorrect because Purview Information Protection encryption settings govern encryption behavior, not the propagation of labels to Power BI exports. Option C is incorrect because setting a workspace default label only assigns labels to new items in that workspace; it does not control label inheritance on exported PDFs. Option D is incorrect because a Purview auto-labeling policy applies labels based on content inspection and does not govern the export-labeling behavior of Power BI reports.

Answer

Enable 'Microsoft Purview Information Protection' file encryption settings.

Answer

Set the default sensitivity label for the workspace to 'Confidential'.

Answer

Configure a Microsoft Purview auto-labeling policy for Power BI reports.

Question 13

You have a date table with columns: Date, Year, Month, Quarter, Day. To enable time intelligence functions like TOTALYTD, what is the minimum requirement?

Accepted Answer

A separate date table with a continuous range of dates and a relationship to the fact table.. The correct answer is A: a separate date table with a continuous range of dates and a relationship to the fact table. Time intelligence functions like TOTALYTD require a dedicated date table that contains an unbroken sequence of dates (no gaps) and is related to the fact table, so the engine can correctly filter and aggregate across time periods. Option B is insufficient because marking a table as a date table is a helpful setting but does not by itself satisfy the structural requirement of a continuous date range and relationship. Option C is wrong because merging date and fact tables into one table breaks the star schema and does not provide the separate date dimension time intelligence needs. Option D is wrong because a single date column in the fact table lacks the continuous, dedicated date dimension required for functions like TOTALYTD.

Answer

Mark the date table as a date table in Power BI.

Answer

Combine date and fact tables into one table.

Answer

A single date column in the fact table.

Question 14

You are building a star schema in Power BI. A fact table contains sales transactions with columns: OrderID, CustomerID, ProductID, Quantity, UnitPrice, Discount, and OrderDate. You need to create a dimension table for customers. Which columns should be included in the Customer dimension?

Accepted Answer

CustomerID, CustomerName, City, Region. A customer dimension should contain the customer's unique key (CustomerID) plus descriptive attributes that describe the customer, such as CustomerName, City, and Region, which are appropriate for slicing and filtering sales facts. In a star schema, the dimension holds only attributes about the entity, while transactional and numeric fields stay in the fact table. Options A and B incorrectly include ProductID and OrderID, which are keys belonging to other dimensions or the fact table, not customer attributes. Option C incorrectly includes OrderDate, which is a date attribute that belongs in a separate Date dimension, not the Customer dimension.

Answer

CustomerID, CustomerName, ProductID

Answer

CustomerID, CustomerName, OrderID

Answer

CustomerID, CustomerName, OrderDate

Question 15

Refer to the exhibit. You apply the above RLS rule to a semantic model. The rule is intended to restrict sales data by the user's region, which is stored in the user's email domain (e.g., user@west.contoso.com). However, the rule does not filter any rows. What is the most likely issue?

Accepted Answer

The filter expression compares the full UPN to the Region column, which likely contains only the region name.. The correct answer is C: the filter expression compares the full UPN to the Region column, which likely contains only the region name. USERPRINCIPALNAME() returns the entire sign-in name such as user@west.contoso.com, so an equality test against a Region value like "West" will never match and no rows are filtered. The rule should instead extract the subdomain or use a mapping table (for example, using SEARCH or PATHITEM-style parsing) to derive the region before comparing. Option A is unlikely because the scenario states the rule is intended to restrict by region and the failure is that it filters nothing, which points to a value mismatch rather than a missing column. Option B is false because USERPRINCIPALNAME() is supported in Power BI for RLS. Option D is incorrect because if the rule were not applied at all, that would be a deployment issue, but the question focuses on the rule's expression logic.

Answer

The Sales table does not have a Region column.

Answer

USERPRINCIPALNAME() is not available in the current Power BI version.

Answer

The RLS rule is not applied to the semantic model.